Generally, many enterprise systems have to handle with a large pool of documents that form the part of their core business. Typically, they contain several pieces of information that may have a structured format but generally having unstructured data as its content. The data contained in these documents are governed by rules as laid out in the operational manual of the core business of the enterprise. Therefore, the data contained in the documents symbolizes syntax and business rules available in an operational handbook of the enterprise. Both the business rules along with the data are present in unstructured natural language text (pool of documents) that in existing approaches is manually interpreted and verified by humans. Moreover, manual verification may take a considerable amount of time and effort when one has to go through a large pool of documents and any human verification and interpretation of rules may be subjected to unavoidable errors.